DISTRIBUTION FUNCTIONS OF RAINFALL ESTIMATES FROM POLARIMETIC MEASUREMENTS AT X-BAND IN TROPICAL BRAZIL

Transcription

1 DISTRIBUTION FUNCTIONS OF RAINFALL ESTIMATES FROM POLARIMETIC MEASUREMENTS AT X-BAND IN TROPICAL BRAZIL Roberto Vicente Calheiros* 1, Maria Andrea Lima* 1, Ana Maria Gomes 1, Paulo Sergio Borges 1 Carlos Frederico de Angelis 2, Izabelly Carvalho da Costa 2 Jojhy Sakuragi 3, Luiz Augusto Toledo Machado 3 1 IPMet/UNESP - Meteorological Research Institute,Bauru - SP, Brazil, calheiros@ipmet.unesp.br 2 CEMADEN - Brazilian Center for Natural Disaster Monitoring and Early Warning, Cachoeira Paulista - SP, Brazil. 3 CPTEC/INPE - Center for Weather Forecasting and Climate Studies, São José dos Campos - SP, Brazil. Roberto Calheiros 1. Introduction * Voluntary Researcher An ever growing interest is taking place in polarimetric radars operating at X-band for specific applications, e.g., rainfall estimates over large urban areas and tracking of fast developing storms. Also, the traditional disadvantage of high attenuation in the X-band is mitigated by the polarimetric approach (Snyder et al. 2010, Marzano et al. 2010). In particular, an X-band network by overcoming the limitations on low altitude coverage and range associated spatiotemporal resolution faced by long range radars, would meet many requirements of rainfall nowcasting e.g. over highly sensitive metropolitan areas. Emblematic to this are the efforts taking place in Japan to deploy operational X-band polarimetric networks in three major metropolitan areas and eight cities (Maki et al. 2010) and the CASA enterprise whose test-bed, known as IP1, is now being deployed as a urban demonstration test-bed in the Dallas-Fort Worth area (Chandrasekar et al, 2011). The Metropolitan Area of São Paulo (MASP), of highest precedence for radar monitoring, has been under surveillance for the first time in the X-band, with the MXPOL radar (Pereira Filho et al. 2007) in the context of the SIHESP( Integrated System of Hydrometeorology of the State of São Paulo) Project. More recently, a polarimetric mobile X-band system integrating the research aimed Chuva Project ( was deployed in the Paraiba Valley, an important area from where it covered the MASP at the outermost range portion of its 100 km surveillance border. The present work follows, in many respects, the methodology in Gorgucci et al. (1995) who pioneered the use of polarimetric measurements in a statistical framework in relation to rainfall estimation. The statistical procedure is based on the probability distribution function matching approach in Calheiros and Zawadzki (1987) adapted to polarimetric data. Firstly, a scatter plot of ZH, ZDR was constructed and an indication of the rain area on the plot was obtained by comparison with previous work (Marzano at al., 2010). From the scatterplot, intervals for both ZH and ZDR were estimated to define the data base to be used for the rainfall computation. In the following, cumulative probability distribution function (CDF) curves for rain rate as derived from radar data and distrometric gauge data are generated. The CDF curves for both sources of data are stratified by daily time intervals, as defined by former research work at IPMet/UNESP (Calheiros and Tepedino, 2006). In Section 2 data sources and data characteristics are presented, while Section 3 contemplates data processing and analysis of results. Section 4 closes the paper with conclusions and future work. 2. Data data is from the X-band polarimetric radar of the Chuva Project as indicated in fig.1 below. The radar antenna beam width is 1.3º and its operational range is 100 km. Reflectivity raw data files are corrected for attenuation generating preprocessed files. The pairs of ZH, ZDR values from the 1.7º elevation PPI extracted from the volume scan constituted the radar data files. Except for a few RHI and 89º elevation PPI scans, data were acquired in 13-elevation volume scans, performed every 6 min. Data period was from 10 November to 28 December Surface rainfall data were from the 3 distrometers identified in fig.1. i.e. IEAV(23.25 S,45.86 W), CESP (23.41 S,45.60 W) and Jambeiro (23.33 S,45.78 W) with a time resolution of 1 minute. Period of distrometric data were from 03 November to 29 December 2011, from 01 November to 31 December 2011 and from 01 November to 28 December 2011 for the CESP, IEAV and Jambeiro sites, respectively. data were from an area restricted to the azimuthal sector from 111º to 133º and to the radial ring from 5 km to 55 km, i.e, to a narrow area covering the distrometer sites.

2 Fig. 1. Chuva Project X-band polarimetric radar at o S, o W, 650m amsl (S. José dos Campos SP) and distrometer sites. Red circle is the 100 km radar coverage range. 3. Analysis and Results The scatter plot of ZH against ZDR is shown in fig.2. The green line corresponds to an average curve drawn by eye on the area classified as rain in fig.1 of Marzano et al. (2010). The authors simulated hydrometeor polarimetric signatures for the X-band. This curve is comparable to that from Al-Sakka et al (2011) for rain. For the purposes of this paper, the range of the polarimetric variables was restricted to 0 ZH 50dBZ and ZDR 0. This is compatible with the scattering simulations of Dolan and Rutledge (2009). The upper limit for ZH and lower limit for ZDR aims to mitigate the contamination from ice and hail. The calculation of rain rates from radar measurement was performed through the following conversion relationship: R( ZH, ZDR) = ZH ( ZDR) where R[mmh -1 ], ZH[mm6m -3 ] and ZDR[dB]. Fig. 2. Scatter plot of ZH against ZDR for the full 1.7 o elevation PPI on 01 December 2011 at 18:53 UTC. The green line corresponds to an average curve on the rain area of fig. 1 in Marzano et al (2010).

3 This relationship was derived by Baquero et al. (2006) using distrometer data to simulate rain rate from a polarimetric X- band radar and to characterize tropical rain, in Puerto Rico. It is specific for convective rain. CDF of rain rate was computed from both the radar and distrometric data for rain rate 200 mmh -1. Figs. 3 and 4 present the resulting curves for radar and distrometer respectively, for the 4 daily intervals adopted in this paper. Rain rate (mmh -1 ) Rain rate (mmh -1 ) 03-09hs 09-17hs 17-22hs 22-03hs 03-09hs 09-17hs 17-22hs 22-03hs Fig. 3. CDF from the polarimetric algorithm in Fig.4. CDF for the indicated in time intervals. Baquero et al (2006), for the indicated daily time Insert details the knee of the curve. intervals. Insert details the knee of the curve. In fig. 3 it is noted that the radar curves are stratified into two groups, one composed of the intervals UTC and 9-17 UTC, and the other of the intervals UTC and UTC. The distrometer curves in fig.4 show a similar behavior, except for the interval UTC. This is the interval when less rain is expected with a correspondingly smaller sample size. In general, the stratification is compatible with that of Calheiros and Gomes (2011). The authors used the Bauru radar whose covered area is contiguous to that of the X-band. However, in their work the curves for the UTC and UTC intervals showed a stratification of hydrological significance. Differences in rain characteristics between the areas of the Bauru and the X-band radar coverage would contribute to this. Figures 5 (a) to (d) present the radar-distrometer sets of curves, one set for each daily interval. (a) (b) Fig. 5. and distrometer CDF stratified by daily time interval, (a) UTC, (b) UTC. Inserts detail the knee of the curves. (c) (d)

4 Fig. 5 (Continued) (c) UTC and (d) UTC. Inserts detail the knee of the curves. The sets of curves for the different intervals exhibit a comparable behavior. The UTC interval is an exception, as discussed before. Table 1 in the sequence shows the relative percent difference of probabilities for the curves at 5 mm/h and 15 mm/h. The relative percent differences in Table 1 remain under 18%, and are larger for the most intense rainfall period of the day. The functional shape of the radar curve for the entire 24h daily period (not shown here) is smoother than that of Gorgucci et al (1995). Table 1. Relative percent differences between radar and distrometer curves for the indicated rain rates, and for the daily time intervals (UTC). Intervals (UTC) Rain rates (mmh -1 ) Conclusions CDF was obtained from polarimetric measurements with an X-band radar in tropical Brazil, through an algorithm developed for a tropical environment. They were plotted against distrometer CDF within the radar coverage area. Curves were stratified by daily time intervals. The scatter plot of ZH against ZDR, presents an area compatible with the rain area in other works dealing with hydrometeor classification. The radar CDF shows, in general, a functional shape comparable to the functional shape of the distrometer CDF. Although the radar algorithm has been developed for another region the radar CDF was close to the distrometer CDF. The radar CDF presented a clear stratification between two sets of time intervals, the first grouping the two intervals of maximum precipitation and the second the two intervals of minimum precipitation. This is, mostly, in agreement with of the behavior of the radar CDF in the central part of the State of São Paulo. In general, the distrometer CDF presents a stratification comparable to that of radar CDF. These preliminary results indicate that the radar algorithm was skillful in stratifying the radar CDF and characterizing rainfall. Future work involves derivation of specific polarimetric algorithms for the set of radar data used in this paper by performing the best matching with the distrometer CDF, and a verification of the impact of stratification of the algorithm by daily time intervals on, e.g, mean radar areal rainfall. References

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